Why is causality important for artificial intelligence?

Michael explains, what we need to understand causal relationships,
he shares examples where people - when analyzing data – often draw
false conclusions on causality based on correlations, and he
provides means to collect data to obtain best possible insights on
causality. The podcast is growing and we want to keep growing.
That's why our German-language podcast is now available in English.
We are happy about new listeners. We thank our new partner
[Siemens](https://new.siemens.com/global/en/products/automation/topic-areas/artificial-intelligence-in-industry.html)
Our guest: https://www.xing.com/profile/Michael_Haft Shownotes:
Glossar AI Definition:
https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact=8&ved=2ahUKEwio2rjL56D7AhXQ8rsIHTiQATEQFnoECBEQAQ&url=https%3A%2F%2Fpublications.jrc.ec.europa.eu%2Frepository%2Fbitstream%2FJRC129614%2FJRC129614_01.pdf&usg=AOvVaw2PL0zIsWsjUF1V_Exqmgxw
Gamechanger:
https://www.amazon.de/Game-Changer-AlphaZeros-Groundbreaking-Strategies/dp/90569181[…]hvdvcmdl=&hvlocint=&hvlocphy=9042437&hvtargid=pla-606747228382